Sprache: Englisch
Verlag: Institute of Physics Publishing, 2022
ISBN 10: 0750322454 ISBN 13: 9780750322454
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
EUR 36,47
Anzahl: Mehr als 20 verfügbar
In den WarenkorbZustand: New. In.
Sprache: Englisch
Verlag: IOP Publishing Ltd Dez 2022, 2022
ISBN 10: 0750322454 ISBN 13: 9780750322454
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Neuware - This research and reference text explores the finer details of Deep Learning models. It provides a brief outline on popular models including convolution neural networks (CNN), deep belief networks (DBN), autoencoders, residual neural networks (Res Nets). The text discusses some of the Deep Learning-based applications in gene identification. Sections in the book explore the foundation and necessity of deep learning in radiology, the application of deep learning in the area of cardiovascular imaging and deep learning applications in the area of fatty liver disease characterization and COVID19, respectively.
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
EUR 153,44
Anzahl: Mehr als 20 verfügbar
In den WarenkorbZustand: New. In.
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
EUR 153,44
Anzahl: Mehr als 20 verfügbar
In den WarenkorbZustand: New. In.
Sprache: Englisch
Verlag: IOP Publishing Ltd Dez 2022, 2022
ISBN 10: 075032242X ISBN 13: 9780750322423
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Neuware - This research and reference text explores the finer details of Deep Learning models. It provides a brief outline on popular models including convolution neural networks (CNN), deep belief networks (DBN), autoencoders, residual neural networks (Res Nets). The text discusses some of the Deep Learning-based applications in gene identification. Sections in the book explore the foundation and necessity of deep learning in radiology, the application of deep learning in the area of cardiovascular imaging and deep learning applications in the area of fatty liver disease characterization and COVID19, respectively.